Data Science for Sports and Physical Activities

lephy2152  2026-2027  Louvain-la-Neuve

Data Science for Sports and Physical Activities
3.00 credits
22.5 h + 15.0 h
Q2
> Schedule
Teacher(s)
Benoit Nicolas; Hardwick Robert (coordinator);
Language
French
Main themes
  • Identification of available data sources that can be analysed (Web databases, applications, etc.),
  • Extracting and converting data into usable files
  • Using concrete examples from different areas of performance,
  • Identification of the main measures used to evaluate individuals and teams, and how they can be formulated and applied.
  • Simplified data processing with Excel
  • Advanced data processing (importing datasets, dataframe, subset, database cleaning, basic statistics, creating a simple function)
  • Data visualisation
  • Creating dashboards
  • Ethical and legal issues relating to the collection and secure storage of of potentially sensitive personal information.
Learning outcomes

At the end of this learning unit, the student is able to :

  • Explain the value of acquiring, managing and analysing data in the context of physical activity practice (1.1)
  • Use the key concepts used in monitoring physical activity and sport (e.g. performance measurements, monitoring participants, workload management, etc.). (1.1, 1.5)
  • Apply data management techniques (spreadsheets, databases, etc.) (1.5, 1.10)
  • Work with data sets (importing files, filtering data for analysis, etc.) (1.5, 1.10)
  • Process data submitted by designers and reproduce transformations (e.g. calculation of VO2 from raw data, calculation of HRV monitoring indicators,
  • Create effective data visualisations (1.5, 1.10, 2.1, 4.1, 7.2)
  • Analyse data to calculate key indicators related to identified concepts (1.5, 1.10, 2.1, 2.2, 4.1, 4.4, 7.2).
  • Demonstrate practical experience in conducting analyses on data sets (2.2)
  • Apply ethical issues such as confidentiality and data security Apply ethical issues such as confidentiality and data security (7.4)
 
Content
This course introduces the principles and practices of data analysis and management in the context of physical activity and sport. Students will explore data sources and learn how to extract, convert, and prepare data for analysis. Through practical examples, the course covers key performance measures for individuals and teams, demonstrating how these can be applied in real-world scenarios.
Participants will gain hands-on experience with both simplified and advanced data processing techniques, including the use of Excel and programming-based methods for importing datasets, cleaning data, applying basic statistics, and creating simple functions. The course also emphasizes data visualization to effectively communicate insights.
Alongside technical skills, students will examine the ethical and legal issues related to data collection and confidentiality of sensitive personal information, ensuring responsible use of data.
Teaching methods
Lectures - practical work
Evaluation methods
       ​☒​  Assessment for this course is based on an exam.
       ​☒​  Exam format :  
                    ​☒​ Theory (R Studio section, 67 per cent): Open-ended questions (written exam on paper)
                    ​​☒​ Practical (Excel section, 33 per cent): Exercises / problems (computer-based exam)
Further useful information:
  • For the practical part of the exam, students must bring their own computer.
  • It is the student’s responsibility to check that their computer has all the necessary software and an internet connection before the exam.
  • The use of AI is permitted during the practical parts of the exam, but not during the theory part.
Other information
This course is strictly reserved for FSM students. It is not open to other UCLouvain students.
Faculty or entity
> FSM


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Motor Skills: Physical Education
EDPH2M
3